Interactive connotative dictionary system

ABSTRACT

A computerized interactive language reference tool is provided which associates one or more connotative meanings with a denotative context of a given term. A data base stores the denotative context and connotative meanings of a plurality of terms. Connotative meaning, along with the intensity of such meaning are identified using a statistical model of sampled responses from select panels of evaluators. Areas of human interest also are associated with a given term and its denotative meaning. Scaled ratings of the power, activity and abstract/concrete qualities of the term also are maintained. Connotative meanings for any given term are determined from predefined emotional descriptors organized into a plurality of predefined categories. The data base content is updated over time to accommodate changing and new connotations occurring over time.

CROSS REFERENCE TO RELATED APPLICATIONS

This invention is related to commonly-assigned U.S. patent applicationSer. No. 09/372,377 filed on the same day, of W. Chase for “System forIdentifying Connotative Meaning;” commonly-assigned U.S. patentapplication Ser. No. 09/372,549 filed on the same day, of W. Chase for“System for Quantifying Intensity of Connotative Meaning;”commonly-assigned U.S. patent application Ser. No. 09/372,244 filed onthe same day, of W. Chase for “Interactive Connotative ThesaurusSystem;” commonly-assigned U.S. patent application Ser. No. 09/372,737filed on the same day, of W. Chase for “System for Connotative Analysisof Discourse.” The content of all such applications are incorporatedherein by reference and made a part hereof.

BACKGROUND OF THE INVENTION

This invention relates to a computerized interactive language referencetool, and more particularly to a system for accessing the connotativemeanings of words and phrases.

Language is an abstract, rule-governed system of arbitrary symbols thatcan be combined in countless ways to communicate information. Alllanguages include a system of phonology (i.e., set of sounds), semantics(i.e., word, phrase and sentence meanings), morphology (i.e., rules forcombining smallest meaningful units to form or alter words), syntax(i.e., ways in which words are organized into phrases and sentences) andpragmatics (i.e., rules governing a conversation and social use oflanguage).

The use of language enables humankind to develop advanced cognitiveabilities. Cognitive development relates to the changes in a person'smemory, thinking, use of language and other mental skills as theydevelop from infants to adults. Humans develop a certain degree ofcognitive competence. In addition to such cognitive competence, humansalso display and experience feelings, emotions and moods. In particular,our emotional state or the emotional state we desire to elicit caninfluence our choice of words. Every human language enables people tocommunicate both intellectually and emotionally because words andphrases convey both cognitive and affective meaning. ‘Affective’ meansto be influenced by or result from emotions.

Linguistics is the scientific study of language. Semantics is the branchof linguistics that deals with the study of the relationship betweenwords or phrases and their meanings. Of particular significance here arethe contrasting linguistic terms, ID denotation and connotation.‘Denotation’ is a particular meaning of a symbol. ‘Connotation’ is anidea or meaning suggested by or associated with a word or phrase. Thus,‘denote’ describes the relation between a word or phrase and the thingit conventionally names, whereas ‘connote’ describes the relationbetween the word or phrase and the images or associations it evokes. Asused herein a denotation is an objective, cognitive meaning which refersto the direct relationship between a term and the object, idea or actionit designates. As used herein, a connotation is a subjective, affectivemeaning which refers to the emotive and associative aspect of a term.

The denotative meanings of words have been systematically codified intodefinitions and collected together to form dictionaries, thesauruses andrelated denotative language references. However, the codification ofconnotative meanings has not been achieved. Consider, for example, adictionary which provides the following denotative meaning for the word‘pub’: “a building providing alcoholic drinks for consumption on thepremises” (Oxford Dictionary). However, the word ‘pub’ simultaneouslyconveys a host of emotional connotations, such as merriment, pleasure,cheerfulness, perhaps some sadness, and so on. Similarly, words such as‘summer’, ‘love’, and ‘melody’ have a variety of positive emotionalconnotative associations for most people, while words such as ‘cancer’,‘rape’, and ‘homeless’ have negative emotional connotations for mostpeople. In all cases, the associated connotations are not systematicallyaccessible using any known language reference resource or tool.

The reason for the absence of codification of connotative meaning isthat, while words readily evoke emotional connotations, the converse isnot true: emotional connotations are not easily codified using words.Unlike denotative meaning, affective meaning does not naturally lenditself to systematic word-symbol description. Emotions are felt, notthought, so the relationship between a word and its associatedconnotative content, while real, is not codifiable using the relativelystraightforward methods employed by lexicographers in fashioningdenotative definitions. Accordingly, there is a need for a connotationlanguage reference tool and a system for codifying the connotativecontent of such a tool.

Not only is it desirable to identify connotative meaning, it also isdesirable to quantify the intensity associated with a connotation. Somewords or phrases evoke stronger responses than others. Some words orphrases are more activity oriented. In the 1950s, Charles Osgood, anAmerican psychologist developed a method of constructing bipolar scalesbased on semantic opposites, such as “good-bad”, “soft-hard”,“fast-slow,” “clean-dirty,” “valuable-worthless,” “fair-unfair,” and soon. Osgood called these scales “semantic differential” scales becausethey differentiated attitudinal intensity based on a person's subjectiveunderstanding of the connotative meanings of words. Osgood et al.explored large amounts of data provided by students who evaluatednumerous words and phrases on numerous semantic differential scales. Theoutcome of Osgood's investigations was a description of the existence of“semantic space,” three measurable underlying attitudinal dimensionsthat proved in subsequent research to be robustly identifiable acrossother languages and cultures. Osgood named these dimensions Evaluation,Power, and Activity (EPA). Experimentation by many investigators aroundthe world confirmed the reality of semantic space and its cross-culturalvalidity (Japan, Scandinavia, Germany, Ireland etc.).

The semantic differential is a method for measuring the meaning of anobject to an individual. It may also be thought of as a series ofattitude scales. A subject is asked to rate a given concept (forexample, ‘Irish’, ‘Republican’, ‘wife’, ‘me as I am’) on a series ofseven-point bipolar rating scales. Any concept—whether it is a politicalissue, a person, an institution, a work of art—can be rated. Subgroupsof the scales can be summed up to yield scores that are interpreted asindicating the individual's position on three underlying dimensions ofattitude toward the object being rated. These dimensions have beenidentified by using factor-analytic procedures in examining theresponses of many individuals concerning many concepts or objects. Ithas been found that three subgroups measure the following threedimensions of attitude: (1) the individual's evaluation of the object orconcept being rated, corresponding to the favorable-unfavorabledimension in more traditional attitude scales; (2) the individual'sperception of the potency or power of the object or concept; and (3) theindividual's perception of the activity of the object or concept. (SeeKidder, L. H., “Research Methods in Social Relations;” 1981).

The problem with the semantic differential technique is that it does notdistinguish beyond a single evaluative continuum, with positive attitudeat one end of the scale through negative attitude at the other end. Thatis, it does not actually identify any individual emotions. Moreover,although several short “semantic differential dictionaries” have beendeveloped (known in the literature as semantic “atlases” because theyare analogous to “maps” of semantic space), consisting of 500 to 1,500words with EPA scores for each word, the technique of semanticdifferential is not associated with any system or method for codifyingthe words of any given language, even on a single affective variable.According there is a need for a system for codifying the connotativemeaning of words.

SUMMARY OF THE INVENTION

According to the invention, a computerized interactive languagereference tool is provided which associates one or more connotativemeanings with a denotative context of a given word or phrase (i.e.,referred to herein as a ‘term’).

According to one aspect of the invention, a data base is generated whichstores the denotative context and connotative meanings of a plurality ofterms. Connotative meaning, along with the intensity of such meaning,are identified using a statistical model of sampled responses fromselect panels of evaluators. In addition, areas of human interest alsoare associated with a given term and its denotative meaning. Further,scaled ratings of the power, activity and abstract/concrete qualities ofthe term also are maintained.

According to another aspect of the invention, the data base content isupdated over time to accommodate changing and new connotations.

According to another aspect of the invention, connotative meanings forany given term are selected from a plurality of predefined categories.In one embodiment described below for the English language there are 8categories. In the preferred embodiment there are four categories ofpositive emotions (e.g., affection/friendliness, enjoyment/elation,amusement/excitement and contentment/gratitude) and four categories ofnegative emotions (e.g., sadness/grief, anger/loathing, fear/uneasiness,and humiliation/shame). Within each category there are a predefined listof emotional descriptors. Thus, there are a plurality of categories ofemotional descriptors. A term may have a connotative meaning in any orall of the emotional categories. Some terms may not have any connotativemeaning. In some embodiments only one emotional descriptor is permittedto be assigned for a given emotional category for a given term. Thus,for an eight category embodiment, any term can have 0 to 8 emotionaldescriptors the emotional descriptors being from different emotionalcategories. In other embodiments a primary and a secondary emotionaldescriptor may be assigned for any given term. For such an embodiment,which is based on 8 emotional categories, any term can have 0-16emotional descriptors—the emotional descriptors being in pairs, with thetwo emotional descriptors in a given pair being for a given emotionalcategory. Different pairs include emotional descriptors for differentemotional categories.

According to another aspect of the invention, for each emotionaldescriptor associated with a given term, there is an intensity rating ofhow strongly or intensely the term tends to promote or relate to theemotional descriptor.

According to another aspect of the invention, a user interface for theconnotative language reference operates in ‘look up’ mode and ‘look for’mode. In ‘look up’ mode a user enters a term and the connotativemeanings are displayed. In ‘look for’ mode a user selects filters tonarrow down the data base to a list of terms meeting the filtrationcriteria.

According to another aspect of the invention, a user interface enables auser to view a selected term and its connotations. In one embodiment theemotional categories are grouped into positive emotions and negativeemotions. The connotative language reference displays the emotionaldescriptors, if any, associated with the selected term relating to thepositive emotions along with their associated intensity level.Similarly, the connotative language reference displays the emotionaldescriptors, if any, associated with the selected term relating to thenegative emotions along with their associated intensity level. Inaddition, the power rating, activity rating and abstract vs concreteratings are displayed along with their corresponding scales.

According to another aspect of the invention, there are a plurality offilters for identifying terms from the database to be displayed. Thereare general filters, such as denotative filters (number of syllables,parts of speech), special diction filters (e.g., slang, euphemistic,interrogative) and non-emotional connotation filters (power, activity,abstract/concrete). There also are human interest filters. There areseveral categories of human interest filters, such as personal identityfilters (e.g., male, female, organization), spiritual identity filters(e.g., Hinduism, Christianity, Myth/legend), physical identity filters(e.g., body, health), perception filters (e.g., taste, place event) andhon-human life filters (e.g., animal, plant). In ‘look for’ mode a userenters selections for one or more filters (e.g, nouns, at least 2syllables, euphemistic, have a power rating of 5 to 8, relating to mythor legend, and relating to health). The terms meeting the criteria ofthe filter selections are displayed, along with the associateddenotative data. A user then can select one of the terms and switch to‘look up’ mode to view the specific connotations associated with suchterm.

According to another aspect of the invention, the connotative languagereference, including the data base, user interface and processingfilters, are stored on a computer readable storage media.

According to one advantage of the invention a large amount ofconnotative and denotative information is accessible to an end user in amanageable format. According to another advantage of the invention, thedata is updated over time for changing connotations. In particular, fora distributed computing model of implementation, such as a globalcomputer network, the content may be updated continually or at varyingintervals.

These and other aspects and advantages of the invention will be betterunderstood by reference to the following detailed description taken inconjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a host computer system;

FIG. 2 is a diagram of a connotative dictionary according to anembodiment of this invention;

FIG. 3 is a display sample of a user interface in ‘look up’ modeaccording to an embodiment of this invention;

FIG. 4 is another display sample of the user interface in ‘look up’ modeaccording to an embodiment of this invention;

FIG. 5 is a display sample of a user interface in ‘look for’ modeaccording to an embodiment of this invention;

FIG. 6 is another display sample of a user interface in ‘look for’ modeaccording to an embodiment of this invention;

FIG. 7 is yet another display sample of a user interface in ‘look for’mode according to an embodiment of this invention; and

FIG. 8 is a diagram of a system for identifying connotative meaningsaccording to an embodiment of this invention.

DESCRIPTION OF SPECIFIC EMBODIMENTS

A system and method are described for identifying, codifying, storing,and retrieving the connotative meaning inherent in the words and phrasesof any language. Throughout this description, a preferred embodiment andexamples given should be considered as exemplars rather than limitationson the method and system of the present invention.

Many of the functions of the present inventions preferably are performedby or with the assistance of a programmed digital computer of the typewhich is well known in the art, an example of which is shown in FIG. 1.A computer system 20 has a display 22, a key entry device 24, apointing/clicking device 26, a processor 28, and random access memory(RAM) 30. In addition there commonly is a communication or networkinterface 34 (e.g., modem; ethernet adapter), a non-volatile storagedevice such as a hard disk drive 32 and a transportable storage mediadrive 36 which reads transportable storage media 38. Other miscellaneousstorage devices 40, such as a floppy disk drive, CD-ROM drive, zipdrive, bernoulli drive or other magnetic, optical or other storagemedia, may be included. The various components interface and exchangedata and commands through one or more busses 42. The computer systemreceives information by entry through the key entry device 24,pointing/clicking device 26, the network interface 34 or another inputdevice or input port. The computer system 20 may be any of the typeswell known in the art, such as a mainframe computer, minicomputer, ormicrocomputer and may serve as a network server computer 12, remotenetwork 16 computer or a client computer 14. The computer system 20 mayeven be configured as a workstation, personal computer, network server,or a reduced-feature network terminal device.

The connotative language reference serves as an interactive electronicconnotative dictionary, thesaurus or other language reference. For aconnotative dictionary embodiment, the connotative dictionary isdistinct from a ‘classic’ dictionary in that it lists words with theirconnotative meanings. For a connotative thesaurus embodiment, theconnotative thesaurus is distinct from a ‘classic’ thesaurus in thatwords are linked when they have the same or a similar emotional orrelated connotative meaning, but typically have a different denotativemeaning. These linked words are referred to herein as “connonyms,” acoined word meaning connotative synonyms. The data bases forming acomputer version of the connotative language references may be formedusing custom-designed database software or database softwarecommercially available from manufacturers such as Inprise, Oracle,Microsoft or another vendor of data base software services.

Following are sections which describe a connotative dictionary, methodsfor identifying connotative meanings, methods for quantifying intensityof connotative meanings, methods for maintaining data integrity, andmethods for identifying human interest areas.

Connotative Dictionary

Referring to FIG. 2, a connotative language reference system 10 isformed by a data base 12, a user interface 14 and various filtering andretrieval processes 16. Preferably such data base 12, interface 14 andprocesses 16 are implemented in electronic format as one or moresoftware programs executed on a host computer system or over a hostcomputer network. For example, the reference system 10 may be stored onan optical disc (e.g., CD-ROM) or other storage media and installed ontothe host computer system or network. Specifically, the data base 12,user interface software 14 and filtering and retrieval processes 16 maybe loaded and installed locally onto the host computer system ornetwork. In some implementations the software embodying the userinterface 14 and processes 16 are installed to be resident on the hostcomputer system or network, while the data base 12 is stored andaccessed from a removable storage media, such as an optical disk. Inother embodiments the data base 12 is centrally located among one ormore network server computers, while the user interface software 14 andprocesses 16 are stored and executed from either a local end usercomputer system or remotely at the server computer. The implementationsmay vary from local copies for a given end user's access to one or morecopies stored on a private network or even a global computer networkwhich users log into to access and use the dictionary.

Data Base 12:

In a preferred embodiment of the data base 12, the data base 12 includesa set of denotative fields 44, a set of connotative fields 46, and a setof human interest fields 48. The denotative fields and human interestfields are not necessary, but provide additional resources for the user.In some embodiments the data base 12 includes only the set ofconnotative fields 46.

The set of denotative fields 44 includes at least two fields, andpreferably three fields. In one implementation the denotative data isobtained from one or more electronic or print-based dictionaries in anylanguage. Database records are created for each word or phrase of thelanguage, which may be the English language or any other language. Insome embodiments the connotative language reference system 10 isspecialized for a given subject (e.g., medical/health contexts;science). In other embodiments a general language reference isimplemented for a given language. Table 1 below lists the desired fieldsincluded among the denotative fields:

TABLE 1 Denotative Field Types 1. Term (i.e., Word or phrase/idiom) 2.Specific denotative context 3. Part of speech (optional, but preferred)

For each record in the data base 12, one denotative field is assigned tothe word or phrase. A second denotative field is assigned to thedenotative context (dictionary meaning) of the word or phrase. A thirddenotative field is assigned to the part of speech. Preferably, eachcontext of each word is assigned a separate database record. Thus, ifthe dictionary definition of a single word has two meanings among atotal of five contexts, then there are five records, one for eachcontext. There may be multiple contexts for a given dictionary meaningwhen, for example, there are different parts of speech for theword/meaning.

Assigning an additional field to track the meanings that subsume thecontexts is not necessary to practice the invention, but such a fieldmay be assigned in an alternative embodiment. The total number ofrecords required is equal to the sum of all of the denotative contextsof all of the words in the dictionary or other denotative data source orsources.

In a preferred embodiment the set of connotative fields 46 includes ablock of one or more fields corresponding to each one of a plurality ofemotional categories. In a best mode embodiment eight emotionalcategories have been identified, although the number of categories mayvary to be more or less than eight. The number of fields comprising eachblock may vary. In one embodiment there is one field in each block thatcorresponds to a primary connotative emotional descriptor for thecorresponding term. In some embodiments there is a field for storing asecondary connotative emotional descriptor for the corresponding term.Note that the primary and or secondary emotional descriptor cancorrespond to a designation of no connotative meaning stored in thisemotional category for the given term.

In addition to the fields for the primary and optional secondaryemotional descriptors, there also are fields associated with each blockrelating to the method for identifying connotative meaning. Although themethod for defining connotative meaning may vary, in one embodiment thedata is collected from multiple sources. In a given implementation thesources are judges or panels of judges. In some embodiments there is afield in each block for each judge's selection of the term's connotativemeaning. In an example, where 24 connotative judges are used, each ofthe eight blocks of fields 46 includes 24 individual fields used inderiving the primary and/or secondary emotional descriptor for theterm—a respective field to hold each judge's emotional descriptor datafor each term in each context. Several additional fields are reserved tohold calculated data based on the connotative judges' emotionaldescriptor data. Fewer or more judges may be used, adjusting the numberof fields within each block accordingly.

Table 2 lists eight emotional categories corresponding to the eightblocks of fields 46 for a best mode embodiment. In the exemplaryembodiment the categories are classified into categories for positiveemotions and categories for negative emotions. The general emotionalclassification “Positive Emotions” subsumes four emotional categories,and the general emotional classification “Negative Emotions” subsumesthe other four emotional categories, as practiced in a preferredembodiment of the invention. Each emotional category subsumes a list ofspecific emotional descriptors (e.g., in this embodiment there are 12 to37 emotional descriptors per category), each of which is associated witha two-digit identifying code number. The specific code number may vary.Further, the manner in identifying the distinct descriptors also mayvary. The total number of emotional descriptors in this example is 164.In various embodiments one or more emotional descriptors may be removedfrom this list, entire emotional categories may be removed from thelist, or one or more emotional categories and descriptors may be addedto this list. In a preferred embodiment it is the code numbers which arestored in the records of the data base 12. In other embodiments theentire emotional descriptor term may be stored individually for eachconnotative data field of a record.

The connotative emotional descriptors that appear in Table 2 are Englishlanguage emotional descriptors for one embodiment of a generalconnotative dictionary. The specific words that make up the emotionalconnotative descriptors may vary. Of course such descriptors will varyfrom language to language.

TABLE 2 Connotative Database Fields POSITIVE EMOTIONS: Affection/Friendliness 01 Adoration 02 Affection 03 Amorousness 04 Devotion 05Fondness 06 Friendliness 07 Infatuation 08 Kindliness 09 Liking 10 Love11 Lust 12 Passion 13 Tenderness 14 Trust 15 Warmth Amusement/Excitement 01 Amazement 02 Amusement 03 Astonishment 04 Eagerness 05Enthusiasm 06 Excitement 07 Exhilaration 08 Exuberance 09 Fun 10 Glee 11Hilarity 12 Merriment 13 Mirth 14 Surprise 15 Thrill 16 WonderEnjoyment/ Elation 01 Admiration 02 Bliss 03 Cheer 04 Delight 05 Ecstasy06 Elation 07 Enjoyment 08 Euphoria 09 Exultation 10 Happiness 11 Joy 12Jubilation 13 Pleasure 14 Pride 15 Rapture Contentment/ Gratitude 01Appreciation 02 Comfort 03 Contentment 04 Gladness 05 Gratitude 06 Hope07 Peacefulness 08 Relief 09 Satisfaction 10 Serenity 11 Thankfulness 12Well-being NEGATIVE EMOTIONS Sadness/Grief 01 Affliction 02 Agony 03Anguish 04 Dejection 05 Demoralization 06 Depression 07 Desolation 08Despair 09 Despondency 10 Disappointment 11 Discourage-  ment 12Dishearten- 13 Disillusionment 14 Dismay 15 Distress 16 Downhearted- ness 17 Forlornness 18 Gloom 19 Grief 20 Heartache 21 Heartbreak 22Heartsickness 23 Hopelessness 24 Hurt 25 Longing 26 Melancholy 27 Misery28 Pain 29 Pity 30 Sadness 31 Sorrow 32 Suffering 33 Torment 34Unhappiness 35 Wretchedness 36 Yearning Fear/Uneasiness 01 Alarm 02Anxiety 03 Apprehension 04 Desperation 05 Distress 06 Dread 07 Fear 08Horror 09 Nervousness 10 Panic 11 Paranoia 12 Stress 13 Tension 14Terror 15 Uneasiness 16 Worry Anger/Loathing 01 Abhorrence 02 Acrimony03 Aggravation 04 Anger 05 Animosity 06 Annoyance 07 Antagonism 08Antipathy 09 Aversion 10 Bitterness 11 Contempt 12 Creepiness 13Detestation 14 Dissatisfaction 15 Disdain 16 Disgust 17 Dislike 18Enmity 19 Envy 20 Exasperation 21 Frustration 22 Fury 23 Hatred 24Hostility 25 Irritation 26 Indignation 27 Ire 28 Jealousy 29 Loathing 30Offense 31 Outrage 32 Rage 33 Rancor 34 Resentment 35 Vexation 36Virulence 37 Wrath Humiliation/ Shame 01 Chagrin 02 Contrition 03Degradation 04 Discredit 05 Disgrace 06 Dishonor 07 Disrepute 08Disrespect 09 Embarrassment 10 Guilt 11 Humiliation 12 Indignity 13Mortification 14 Regret 15 Remorse 16 Shame 17 Stigma

In a preferred embodiment each record also includes a set of humaninterest fields 48 which relate the corresponding term and itsdenotative context to a human interest category. The purpose ofincorporating the human interest fields is to permit the end user toeasily retrieve special connotative content from the database by firstselecting one or more human interest filters before querying thedatabase. The human interest fields 48 employed in an exemplaryembodiment of the invention are listed in Table 3. There are ninegroupings of the human interest categories in such embodiment. Eachrecord includes a set of nine human interest fields—one field for eachhuman interest category. Each field stores a human interest descriptorword. Of course, the field also may store a designation that there is nohuman interest context for the term as used in the associated denotativecontext of a given record. The human interest categories and descriptorsmay vary from embodiment to embodiment.

TABLE 3 SET 3: Human Interest Database Fields Non-emotional ConnotationsPower Activity Rhythm Number of Syllables Accented Syllable SpecialDiction Question-starting Words Core Words Identified by S. I. HayakawaPersonal Identity Gender First Names (Baby Names) Notorious OrCelebrated People Languages National Identity Organizations of Note HomePersonal Relationships Intimacy Spiritual Identity Biblical DictionChristianity Judaism Islam Hinduism Buddhism Other Religious Myth andLegend Paranormal Physical Identity Physical Appearance Body HealthPerception Abstract/Concrete Continuum Place, General Place, EventPlace, Transportation Place, Cosmos Place, Noted Color Hearing TouchTaste Smell Time, General Time, Historical Time, Calendar Non-medicalDrug Use Non-human Life Animals Plants Micro Organisms Argot/VernacularSlang Taboo Offensive Derogatory Disgusting/Revolting Euphemistic Cliche

In a preferred embodiment of the invention, the assignment of the fieldsand records as described above effectively links each traditionaldictionary definition of each term in each context with more than 200connotative and human interest variables. The data base may be organizedinto one or more tables, files or other units of organizing data.Regardless of the number of tables or files, there are entries from eachtable or file which correspond to a term (i.e., a word or phrase amongthe denotative fields). The data associated with any given term isreferred to herein and in the claims as a ‘record’, whether or notcoming from a single table or file, or from multiple tables or files.Each record includes a field which identifies a term and another fieldwhich identifies the denotative context for the term. The record alsoincludes a field which identifies the connotative meaning. Thus, eachrecord includes at least three fields allocated among 1 to 3 tables,files or other units of organization of the data base. In a preferredembodiment there are a plurality of connotative meaning fields, at leastone for each of a plurality of emotional categories. The connotativemeaning fields identify an emotional descriptor for a correspondingemotional category. Such identification may be an identification of aspecific emotional descriptor within the corresponding category or anindication that there is no emotional descriptor for such category. Anindication of no connotative meaning is still considered to beconnotative meaning information.

In varying embodiments additional fields are included for any one ormore of the following types of information: parts of speech, intensityof connotative meaning, power rating, activity-rating, abstract/concreterating, human interest areas. When an intensity field is included theintensity is an intensity of a connotative meaning and is associatedwith a corresponding emotional category and the identified emotionaldescriptor for such category.

User Interface 14:

In a preferred embodiment a graphical user interface is implemented,which provides an end user with the capability of retrieving data fromthe data base 12. Although there are many ways in which a user interfacemay be implemented, in one embodiment a system with menus and windows isused.

In one embodiment the user interface 14 is operated in differentmodes—‘look up’ mode or ‘look for’ mode. During ‘look up’ mode a userenters a word or phrase and data is retrieved from the database 12 anddisplayed to the user. In ‘look for’ mode a user enters parameters intovarious filtering processes which are implemented to retrieve wordswhich meet the parameters.

FIG. 3 shows an embodiment of the graphical user interface 14 in ‘lookup’ mode. The mode is indicated on a button 50 in the upper right cornerof the interface window 52. When in ‘look up’ mode, the user may type aword or phrase into a ‘look up’ box 54 in the upper left corner of theinterface window 52. The connotative dictionary responds to the user'styped input by retrieving denotative information from the database 12relating to the word or phrase that has been typed into the ‘look up’box 54. This denotative information is displayed alphabetically in anarea 55 (e.g., column) on the left-hand side of the user interface, andis formatted in much the same manner as the same denotative informationis displayed and formatted in any conventional electronic dictionary.

Simultaneously, the dictionary 10 retrieves from the database 12 anddisplays on display 22 a range of connotative information relating tothe same word or phrase that the user has typed in the ‘look up’ box 54.This connotative information is displayed in an area 57 on theright-hand side of the user interface window 52.

Although specific formats and locations are being described the specificformat and location of information within the window 52 may vary. In oneembodiment the connotative information is displayed in a color-codedgraphical format, including horizontal bars. Preferably, the relativelengths of the horizontal bars represent data corresponding toconnotative intensity (strength or weakness). For the power, activityand abstract/concrete information, the relative length represents arating along a scale. In one example, the colors designate thefollowing:

Green (56) Positive emotional connotations Red (58) Negative emotionalconnotations Grey (60) Connotations of power Yellow (62) Connotations ofactivity Olive (64) Connotations of abstractness or concreteness

A set of two tabs 61, 63, labeled “Level 1” and “Level 2,” indicate thelevel of emotional classification and categorization of the connotativedata represented in the graphical display area 57, 59 associated withthe selected tab. In one embodiment these levels of classification andcategorization are defined as follows:

Level 1: Four level 1 categories of “Positive Emotions” and four level 1categories of “Negative Emotions” for the embodiment illustrated in FIG.3.

Level 2: Each level 1 emotional category subsumes a list of 12 to 37specific emotional descriptors (e.g., level 2 information), as listed inTable 2. Only the level 2 emotional descriptors associated with the worddisplayed in the ‘Look up’ box are displayed.

FIG. 4 shows the user interface 14 in ‘look up’ mode with the level 2data being displayed in window area 59. Such window area 59 overlaysarea 57 when tab 63 is selected. In one embodiment the window area 59includes a plurality of display placeholder variables 65. There is aplaceholder variable for each one of the emotional categories. When arecord is displayed the emotional descriptor for the correspondingcategory for the given record is displayed (when there is an emotionaldescriptor for such category for such record). Thus, rather than see aname of an emotional category in window area 59, the emotionaldescriptor corresponding to that category is viewed. Note that in theexample illustrated, there is only one emotional descriptor (i.e.,‘excitement’) in FIG. 4 for the positive emotion categories (of FIG. 3).Accordingly, there was no connotation for the other three positiveemotional categories. Also shown is a horizontal bar. The length of thebar corresponds to the intensity of such emotional descriptor for theconnotation to the term looked up. A scale 67 for the intensity isincluded in the window area 57.

FIGS. 5-7 show the user interface 14 in ‘look for’ mode. The user enters‘look for’ mode by toggling the ‘Look up/Look for’ toggle button 50. Ina preferred embodiment of the invention, switching to “Look for” modechanges the window 52 format to display a set of three tabs 66, 68, 70and corresponding to overlaying window areas 72, 74, 76. These tabs 66,68, 70 and window areas 72, 74, 76 replace the tabs 61, 63 and windowareas 57, 59 of ‘look up’ mode.

In ‘look for’ mode the user may retrieve connotative content from thedatabase 12. First, the user selects criteria from one or more humaninterest filters or the non-emotional information (power, activity andabstract/concrete). Then the user initiates a search of the data base 12for records matching the criteria. The human interest fields 48 employedin a preferred embodiment of the invention are listed in Table 3. Thesefields are displayed among the window areas 72, 74,76 and accessed bypressing on the corresponding tab 66, 68, or 70. The number of tabs 66,68, 70 and the allocation of human interest fields 48 to the windowareas 72, 74, 76 may vary.

In one embodiment the human interest fields associated with tab 66 arethe special diction fields, the argot/vernacular fields and thenon-emotional connotation fields of Table 3. In addition there aredenotative filters 80 included in window area 72 for defining selectioncriteria. The user can search specific definitions, limit the words andphrases or parts of speech, limit the number of syllables or theaccented syllable using the denotative filters 80. The user can selectamong slang, coarse, derogatory and other types of diction andvernacular under the heading of special diction filters 82. Thenon-emotional connotation filters 84 relate to scaled values based on apower, activity or abstract/concrete.

Referring to FIG. 6, window area 74, which is selected by pressing ontab 68, includes personal identity filters 86, spiritual identityfilters 88 and physical identity filters 90. In the example illustrated,the user has specified a filtered search of the database for a randomselection of famous or notorious female persons. The language referencesystem 10 retrieves the requested information and displays it in thewindow 55 on the left-hand side of the user interface, once the userfinalizes the choices by clicking on the button labeled ‘OK.’

The user may select several human interest filters for a single search,in order to retrieve very particular customized lists of words andphrases. In a preferred embodiment of the invention, when the user hasretrieved a customized list, the user may then switch back to “Look up”mode and retrieve all of the connotative information associated with anyof the words and phrases in the customized list.

The human interest fields associated with the third tab in “Look for”mode are displayed in FIG. 7. In the example illustrated, the user hasspecified a filtered search of the database 12 for a random selection ofnoted places. The apparatus retrieves the requested information anddisplays it in the window on the left-hand side of the interface.

In a best mode embodiment the data base is stored on a computer readablestorage media, such as embedded memory, RAM, ROM, a hard disk, anoptical disk, a floppy disk, magneto-optical disk, electro-optical disk,or another known or to be implemented transportable or non-transportablecomputer readable storage media. The user interface, processing filtersand other executable instruction code for maintaining and accessing thedata base also is stored on the same or another computer readablestorage media of the types listed above.

Under various computing models, the connotative language reference isinstalled at an end user computer or accessed remotely from an end usercomputer. For resident computing models, the executable instructions maybe loaded onto the computer and the data base accessed from atransportable storage media. Alternatively the data base also may beinstalled locally. One skilled in the art will appreciate the manycomputing configurations that may be implemented. For non-residentcomputing models, the data base may be stored at a server computer on apublic or private, local or wide area network, or even on a globalcomputer network. The executable instructions may be run either at theend user computer or at a server computer with the data being displayedat the end user's display device.

Identifying Connotative Meaning

According to a preferred embodiment of the invention the connotativemeanings associated with the terms found in the connotative languagereference system are derived by subjective responses from a plurality ofevaluators. In a best mode embodiment the evaluators are a panel ofpersons having objective credentials or accepted expertise inconnotative analysis. However, in some embodiments the evaluators may beselected at random. Such persons are referred to herein as connotativejudges. In a preferred embodiment, the Internet is used as a recruitmentmedium to recruit 100 to 200 individuals who are not known to each otherto act as independent connotative judges. In one embodiment, theconnotative judges are screened for the following characteristics listedbelow in Table 4:

TABLE 4 Characteristics and Qualifications of Connotative Judges 1. 25%of all judges aged 40 or older and female 2. 25% of all judges under theage of 40 and female 3. 25% of all judges aged 40 or older and male 4.25% of all judges under the age of 40 and male 5. All judges having atleast 2 years of post-secondary education 6. All judges having anabove-average vocabulary and command of whichever language is being usedto practice the invention. 7. All judges having a substantial interestand some experience in the craft of writing, preferably creativewriting. 8. Judges geographically dispersed over the area of interestfor the language of interest.

While the above qualifications are used in one embodiment, the inventionmay be practiced using any number of judges having any qualifications ofone's choosing. For example, connotative judges may be only women, oronly men, or only individuals of a defined age or ethnic group, or onlypeople who reside in a certain geographical location. The nature andquality of data captured will of course vary with the demographicprofile of connotative judges, as well as with the number of judges usedwhen practicing the invention, their geographical locations, and thelinguistic qualifications of the judges.

The connotative judges evaluate the meaning of given words and phrasesfor connotative content using a questionnaire. The questionnairespreferably are distributed as database software files, although they mayalso be distributed in paper document form. The responses of theconnotative judges are processed using either custom-designed databasesoftware or database software commercially available from manufacturerssuch as Inprise, Oracle, and Microsoft. As the data are analyzed, adatabase of connotative meaning is constructed, which is linked witheach context of each word in the connotative dictionary. Eachquestionnaire is, in effect, a small database table containing five datafields, as summarized in Table 5.

TABLE 5 Data Fields for Questionnaire Tables to Capture Connotative DataField 1 A field containing a term selected at random from the term fieldof the main database Field 2 A field containing the denotative contextfor the term in Field 1 Field 3 A field containing the part of speechfor the term in Field 1 (optional but preferred) Field 4 A blank fieldassigned for the connotative judge to record data identifying emotionalconnotations associated with the term and context in Fields 1 and 2Field 5 A blank field assigned for the connotative judge to record datacorresponding to intensity of emotion associated with the term andcontext in Fields 1 and 2

Field 4 is used for identifying connotational meaning. Field 5 is usedfor identifying the intensity of the connotation. The use of Field 5 isdescribed below in the section, Quantifying Intensity of ConnotativeMeanings.

In one embodiment, a distributed computing model is employed, in whichthe connotative judges use their own computers in their own homes oroffices to receive questionnaire tables over the Internet (via e-mail orfrom a World Wide Web site) that are extracted from the main database12. The connotative judges complete their work on the questionnairetables, and then return the data tables over the Internet.

Referring to FIG. 8, a pool 80 of connotative judges are recruited toevaluate records of the connotative data base 12 for connotativeassociations of corresponding words and phrases. A sample of judges fromthe pool 80 forms a panel 82 used to evaluate a set of records. The sameor different panels are formed to evaluate other sets of records. Thenumber of records in a set may vary. For purposes of illustration apanel of 24 judges is described which evaluates a set of 500 records. Ina preferred embodiment, each judge typically receives a questionnairetable 84 covering approximately 500 records, each record consisting ofthe four fields identified in Table 4. The questionnaire laso includesinstructions for selecting a code number to fill in the blank Field 4for each record. Each connotative judge is also supplied with one ormore of the eight category lists of code-numbered emotional descriptorsidentified in Table 2. In a preferred embodiment for a givenquestionnaire each judge is supplied with only one of the eight categorylists of emotional descriptors found in Table 2. Thus, in a givenquestionnaire a judge evaluates the terms for connotative meaning inonly a specific emotional category. To complete the questionnaire table,the connotative judge inputs one of three codes or code types for eachrecord in Field 4, as listed in Table 6.

TABLE 6 Coding Alternatives for Capturing SET 2 Connotative Data 1. Codethe two-digit number (see Table 2 above) associated with one and onlyone emotional descriptor that most closely matches the emotionalconnotation that the connotative judge associates with the term in Field1, considering the denotative context and part of speech in Fields 2 and3. 2. Code “00” if the connotative judge understands the term and itsdenotative context, but does not associate any of the emotionaldescriptors from the supplied list of emotional descriptors with theterm and its denotative context. 3. Code “99” if the connotative judgedoes not know the term, or the specific associated denotative context.

In a preferred method of practicing the invention, only one judgment isrequired for each record in a questionnaire table. However, in otherembodiments more than one judgment may be allowed or required, if, forexample, one wishes to capture the connotative judge's first choice andalso the connotative judge's second choice of emotional descriptor. Toeffect such data capture, the number of connotative fields 46 (see FIG.2) would need to be expanded accordingly, and the questionnaire tablestructure modified to include additional data capture fields.

The connotative judge repeats this procedure for all 500 records in thequestionnaire, then returns the completed questionnaire table 84 via theInternet. Thereafter, the judge may receive another questionnaire table86, or 88 to evaluate. The next questionnaire table received by theconnotative judge may contain exactly the same set of records that wasjust evaluated, but accompanied by a different category list ofemotional descriptors to be used for coding. Alternatively, the nextquestionnaire table may contain a completely different selection ofrecords. The exchange of questionnaire tables continues iteratively forthe duration of connotative data collection.

In a preferred embodiment of the invention, each block of 500 records isevaluated in this manner eight times (corresponding to the eightcategory lists of connotative descriptors listed in Table 2), each timeby 24 different connotative judges selected at random from the pool of100 to 200 available connotative judges, using a judge-selectiontechnique that stratifies sampling to ensure equal representationaccording to the guidelines summarized in Table 4. Note that the numberof judges selected, the size of the pool and the number of recordsprocessed in a given questionnaire may vary.

Typically a plurality of panels 82, 83 are formed to evaluate thedatabase 12 records for connotative associations. Different panels 82,83 receive either the same or different questionnaires 84-89. For theexemplary embodiment where 24 judges evaluate each of 500 records in agiven questionnaire, the same 24 judges may or may not evaluate alleight categories of emotional connotations for such 500 records.

Quantifying Intensity of Connotative Meanings

As previously described each judge receives a questionnaire. In oneembodiment the questionnaire is in table format. Each record in thetable has multiple fields as listed above in Table 5. Fields 1, 2 and 3are already complete and correspond to the term, a denotative contextfor such term, and a part of speech. Field 4 is filled in as describedabove to identify connotative meaning for the term. Field 5 is to befilled in to record the intensity associated with the connotativemeaning provided in Field 4. When a judge indicates that there is noconnotative meaning for the term or that the judge does not know theterm or the specific denotative context, then there is no need toquantify an intensity in Field 5. Where a judge is permitted to providetwo connotative meanings (e.g., a primary and a secondary connotativemeaning) then additional fields are included for each record in thequestionnaire (e.g., two fields corresponding to Field 4 and two fieldscorresponding to Field 5).

Typically a judge quantifies the intensity of the connotative meaningwhen selecting the connotative meaning itself. The intensity is a scaledvalue judgement of the judge. Table 7 lists the ratings scale for oneembodiment.

TABLE 7 General Coding Model for Capturing Field 5 Data 1 2 3 4 5 6 7slightly very intense intense 0 = automatically coded, corresponding to‘00’ code entry in Field 4 9 = automatically coded, corresponding to‘99’ code entry in Field 4

In a preferred embodiment, a guiding set of anchor terms are includedwhich are prerated for intensity. The judge's review of such guiding setimproves consistency and accuracy among many judges completing thequestionnaires. Specifically, the anchor terms are terms that areassociated with scale numbers that represent the average intensityscores that other people have provided for various terms. Eachconnotative judge is expected to disagree with some of the scoresrepresented by some of the anchor terms. For this reason, connotativejudges are instructed to either, (i) highlight only those anchor termswith which they are comfortable, or (ii) alternatively, cross out thoseanchor terms with which they are uncomfortable. The connotative judgethen compares the term he or she is scaling in the questionnaire tablewith his or her intensity of feeling associated with the anchoredscales, choosing the scale number with the closest match.

The anchor terms are representative averages; they do not imply“correctness,” but rather provide the connotative judge with indicatorsof the relative strength of feeling that the connotative judgeassociates with the chosen emotional descriptor that is meant to beassociated with each score number. In effect the anchor terms serve as away for the judges to calibrate themselves to a scale of intensity.Table 8 presents a typical list of anchor terms associated with a groupof emotional descriptors subsumed under the emotional category‘Sadness,’ which is one of the eight emotional categories previouslydescribed.

TABLE 8 Anchor Terms for Scaling Intensity of Connotative Feeling forthe Emotional Category “Sadness” SCALE LEVEL 7 (very intense sadness) 1.Holocaust - n the mass murder by the Nazis of the Jews of continentalEurope between 1940 and 1945. 2. Auschwitz - n Polish town, site of aNazi death camp during World War II. 3. child abuse n physical, sexual,or emotional ill-treatment or neglect of a child by parents or otheradults. 4. AIDS - n acquired immune (or immuno-) deficiency syndrome. 5.rape victim - n a person who has suffered rape/sexual attack 6. starvingperson - n a person whose health is deteriorating from lack of food 7.murder - n the unlawful premeditated killing of one human being byanother 8. cancer - n malignant growth or tumor; uncontrolled celldivision 9. suicide - n the act or an instance of killing oneselfintentionally 10. death - n the permanent end of all functions of life11. blind - adj unable to see; sightless 12. insane - adj mentallyderanged; crazy; of unsound mind SCALE LEVEL 6 1. slave - n a personhaving no freedom and forced to work for another. 2. abused person - n aperson who is maltreated, esp. physically or sexually. 3. leukemia - nan acute or chronic disease characterized by a gross proliferation ofleucocytes; cancer of the blood. 4. abandon - v to forsake completely;desert; leave behind 5. child pornography - n sexually explicitwritings, pictures, films, etc., of children designed to stimulatesexual excitement. 6. depression - n a mental disorder characterized byextreme gloom, feelings of inadequacy, and inability to concentrate 7.divorce - n the dissolution of a marriage by judgment of a court. 8.starve - v to die or cause to die from lack of food. 9. lonely - adjunhappy as a result of being without the companionship of others 10.heartless - adj unkind or cruel; hard-hearted 11. hurt - adj injured orpained physically or emotionally 12. suicidal - adj involving,indicating, or tending towards suicide SCALE LEVEL 5 1. beggar - n aperson who begs, esp. one who lives by begging. 2. sufferer - n a personwho is undergoing pain, punishment, etc. 3. leper - n a person who hasleprosy. 4. victimize - v to punish or discriminate against selectivelyor unfairly. 5. lose - v to be without, as through theft, accident,negligence, etc. 6. degrade - v to reduce in worth, character, etc.;disgrace; dishonor. 7. desert - v to leave or abandon, esp. in violationof a duty, promise. 8. deprive - v to prevent from possessing orenjoying; dispossess (of). 9. alienate - v to cause to becomeindifferent, unfriendly, or hostile; estrange. 10. demoralize - v toundermine the morale of; dishearten. 11. pain - n emotional, mental, orphysical suffering or distress. 12. missing - adj not able to be tracedand not known to be dead. SCALE LEVEL 4 1. inmate - n a person confinedto an institution such as a prison or hospital. 2. drunkard -n a personwho is frequently or habitually drunk. 3. addict -n a person who isaddicted, esp. to narcotic drugs. 4. haunt - v to intrude upon or recurto (the memory, thoughts, etc.) 5. condemn - v to express strongdisapproval of; censure. 6. refuse - v to decline to accept (somethingoffered). 7. skid row - n a dilapidated section of a city inhabited byvagrants, etc. 8. hopeless - adj having or offering no hope. 9. alone -.adj apart from another or others; solitary. 10. persecuted - adjoppressed, harassed, or maltreated. 11. unemployed - adj withoutremunerative employment; out of work. 12. deformed - adj disfigured ormisshapen. SCALE LEVEL 3 1. wino n a person who habitually drinks wineas a means of getting drunk. 2. wretch n a person pitied for theirmisfortune. 3. tracks n needle marks on the skin of an injection druguser. 4. ostracize v to exclude or banish (a person) from a particulargroup, society. 5. forsake v to give up (something valued or enjoyed).6. jail n a place for the confinement of prisoners. 7. lonely adjunhappy as a result of being without companionship of others. 8. hungryadj experiencing pain, weakness, or nausea through lack of food. 9.rejected adj not accepted, acknowledged, used, believed, etc. 10.pitiful adj arousing or deserving sympathy or sorrow. 11. helpless adjunable to manage independently. 12. let down adj unfulfilled inexpectations; disappointed. SCALE LEVEL 2 1. drop-out - n a student whofails to complete a school or college course. 2. lush - n a heavydrinker, esp. an alcoholic. 3. underestimate - v to think insufficientlyhighly of. 4. flophouse - n a cheap lodging house, esp. one used bytramps. 5. God Bless the Child - n a song written by Billie Holiday andArthur Herzog. 6. homesick - adj depressed or melancholy at being awayfrom home and family. 7. lost - adj confused, bewildered, or helpless.8. empty - adj without purpose, substance, or value. 9. heavy hearted -adj sad; melancholy. 10. disenchanted - adj disillusioned. 11. unlucky -adj characterized by misfortune or failure. 12. blue - adj depressed,moody, or unhappy. SCALE LEVEL 1 (slight sadness) 1. wallflower - n aperson who stays on the fringes of a dance or party. 2. gambler - n aperson who risks or bets (money) on games, sports, etc. 3. orphan - n achild, one or (more commonly) both of whose parents are dead. 4.runaway - n a person who takes flight or escapes. 5. dim - v to cause toseem less bright, as by comparison. 6. coal mine - n a system ofexcavations made for the extraction of coal. 7. mobile home - n livingquarters mounted on wheels and capable of being towed. 8. Monday - n thesecond day of the week; first day of the working week. 9. comb-over - na hairstyle in which long hair from the fringes of the scalp is arrangedto cover and hide a bald portion of the scalp. 10. colorless - adj greyor pallid in tone or hue. 11. indifferent - adj showing no care orconcern; uninterested. 12. resigned - adj acquiescent or submissive.(NOTE: the numbers 1 through 12 for the anchor terms are merely forreference purposes. NO RANK ORDER is implied by the numbering within ascale level.)

A judge looks at each anchor term for a given rating in a givenemotional category of the categories listed in Table 2. The judgeselects one or more anchor terms under a given rating for a givenemotional category which the judge feels most closely relates to theintensity rating subjectively felt by the judge.

In a preferred embodiment, the anchor terms are updated over time basedupon many judges' response entries into Field 5 for each record. Inparticular the Field 4 and 5 entries are analyzed to identify termswhich consistently are judged by many different judges to have the sameconnotative meaning and the same intensity. Such terms become reliableanchor terms. This is done on an ongoing basis in order to build up alarge, reliable database of anchor terms.

As indicated above, an 8-point scale (including zero, indicating absenceof the specified connotative feeling) is used to capture data for Field5 in a preferred embodiment of the invention. However anchored scales ofsmaller or larger size, such a 3, 5, or 9 point scales may be used.Also, the number of anchor words or phrases may be greater than the 12used in the preferred method, or fewer than 12. The number of anchorterms should be large enough to allow a choice permitting theconnotative judge to select only those with which he or she iscomfortable.

The connotative judge repeats the above steps to input data for Fields 4and 5 for all records in the questionnaire, then returns the completedquestionnaire table via the Internet, then receives anotherquestionnaire table to evaluate. The next questionnaire table receivedby the connotative judge may contain exactly the same set of terms thatwas just evaluated, but accompanied by a different list of emotionaldescriptors to be used for coding Field 4, and a correspondinglydifferent set of anchors for coding Field 5. Alternatively, the nextquestionnaire table may contain a completely different selection ofterms, with a corresponding emotional descriptor list for Field 4 and ananchor term list for Field 5. The exchange of questionnaire tablescontinues iteratively for the duration of connotative data collection.

In a preferred embodiment of the invention, each block of 500 records isevaluated in this manner eight times, corresponding to eight emotionalcategories, each time by 24 different connotative judges. In thismanner, a full-language dictionary database in any language, associatingevery context of every word with a very broad range of identifiedemotional connotations and their individual intensity levels, isconstructed.

Data Integrity

Comparatively analyzing the connotative data associated with each blockof records being processed serves to check for data integrity. Checkingthe data for integrity is part of an automated questionnaire processingfunction 90 (see FIG. 8) . An initial integrity processing step is todetermine whether any of the 24 sets of data should be rejected asinvalid because of anomalous data. This is accomplished by statisticallycomparing the score set of each individual judge with the combined scoresets of the other 23 judges who evaluated the same set of words usingthe same lists of emotional descriptors. If the scores between any givenjudge's data and the aggregate data of the other judges in the panel arenot statistically related, then the data set for the anomalous judge isrejected. Anomalous data may arise if, for example, a connotative judgeis filling in random data to avoid the mental work involved in providinggenuine connotative data, or if a judge is coding a large number ofdouble zeros and ninety-nines, or if a judge's experience is so far outof the mainstream that his or her connotative associations are notrepresentative of the larger population. In a preferred method ofpracticing the invention, a minimum correlation level of 0.6 is used asa data rejection threshold.

Further analysis includes determining how many valid non-zero scoresremain after purging invalid scores and after accounting for 00 and 99scores. A determination is then made to ascertain which emotionalconnotations the judges most often associate with each word or phrase.This is a function of four factors:

1. The number of valid scores remaining after data purging;

2. The number of emotional connotative descriptors in the list thejudges had to choose from;

3. The number of judges who selected the same emotional descriptor; and

4. The probability that the same emotional descriptor was selected bymore than one judge merely by chance.

The multinomial probability distribution below in equation (I) embodiesthe above factors: $\begin{matrix}{{P(y)} = {\frac{n!}{{y!}{\left( {n - y} \right)!}}*p^{y}q^{n - y}}} & (I)\end{matrix}$

where:

n is the total number of independent connotative judges evaluating therecord;

y is the number of judges selecting a particular emotional descriptor;

p is the probability of the emotional descriptor being selected if theselection occurs by chance;

q is the probability of an emotional descriptor being excluded if theselection occurs by chance; and

P(y) is the probability of the emotional descriptor being selected by yjudges if the selections occurred by chance.

Tables may be constructed of the probabilities P(y) of connotativejudges independently selecting the same emotional descriptors by chancefor various panel sizes (e.g., increasing incrementally up to 24, and/oradditional panel sizes of 36, 72, 96, 120 or any other panel size), andemotional connotative descriptors available for selection (e.g.,increasing incrementally up to 24, with additional category group sizesof 36, 72, 96, 120 or any other corresponding descriptor group size).

As an example, consider the following set of connotative judgments forone word evaluated by 24 connotative judges on the Amusement/Excitementemotional category, which subsumes 16 emotional descriptors. The totalnumber of valid judgments after purging is 21 (Table 9).

TABLE 9 Example of Field 4 and 5 Questionnaire Table Scores EmotionalField 4 “Votes” Received Field 5 Descriptors from Connotative JudgesIntensity Scores Amazement 0 Amusement 3 5, 3, 5 Astonishment 0Eagerness 2 5, 4 Enthusiasm 0 Excitement 1 4 Exhilaration 1 5 Exuberance1 4 Fun 0 Glee 5 3, 4, 6, 4, 4 Hilarity 3 4, 4, 5 Merriment 1 5 Mirth 36, 4, 5 Surprise 0 Thrill 1 4 Wonder 0

The associated probabilities of chance selection of the same emotionaldescriptor by independent connotative judges, according to equation (I),are as follows:

Number of Judges Selecting Probability of the Same Category ChanceSelection 0 0.258 1 0.361 2 0.241 3 0.102 4 0.030 5 0.007

In this example, only one emotional descriptor, “Glee,” has beenselected by enough independent connotative judges (5 judges) to meet thetest of statistical significance, and is retained in the main database12 as a connotative association for the term being evaluated. For anygiven term, selection of emotional descriptors from one emotionalcategory does not preclude selection of emotional descriptors from otheremotional categories. Any given term is apt to evoke several kinds ofemotional response simultaneously. Therefore, the same term is alsoevaluated in an identical manner on the other seven categories ofemotional connotations listed in Table 2. Thus, the term may, or maynot, finish with more connotative emotional descriptors added when thedata collection procedure has been completed.

In a preferred embodiment of the invention, terms that receive no votesfrom the connotative judges on any of the connotative groupings, or toofew votes on all eight connotative groupings to meet the test ofstatistical significance, are tagged as A“non-connotative,” so that suchterms may be optionally excluded from further analysis or databasequerying.

As for connotative intensity, all 21 scores in the above example arevalid, not just the 5 scores for the specific emotional descriptor“Glee,” because the 21 Field-5 scores represent the general emotionalcategory, “Amusement/Excitement,” which subsumes the specific emotionaldescriptor, “Glee.”

By completion of data analysis, each of the eight emotional variablescontains one mean (i.e., average) intensity score for each word orphrase. An unbiased estimate of the variance of the sample of 21anchored intensity scores in Table 9 is calculated according to thefollowing variance formula:$s^{2} = \frac{\sum\left( {X - \overset{\_}{X}} \right)^{2}}{\left( {n - 1} \right)}$

from which the standard error of the mean for the sample is estimated inaccordance with the following formula:$\frac{s}{x} = \frac{s}{\sqrt{n}}$

where:

X is an independent connotative judge's score {overscore (X)} is thesample mean n is the number of scores in the sample s² is an unbiasedestimate of the variance of the sample s is the sample standarddeviation s_({overscore (x)}) is the standard error of the mean.

In the present example, the average of the 21-score sample of Field-5data presented in Table 9 is 4.4. The standard deviation of the 21-scoresample is approximately 0.81, which, when divided by 21 yields astandard error of the mean of about 0.177, for a 95% confidence levelabout the mean of ±0.35. Further accuracy is obtained by programming thecomputer to identify and purge “outlier” scores. This is accomplished bycomparing each score with the mean and purging scores that are higher orlower than a statistically specified distance from the mean.

In a preferred embodiment of the invention, terms that receive noField-4 emotional descriptor votes from the connotative judges on any ofthe eight emotional categories (and therefore no Field-5 intensityscores) are tagged as “non-connotative,” so that, at the user's option,such terms may be excluded from further analysis or database querying.

Identifying Human Interest Area Relating to a Record

The Human Interest fields 48 may be defined in the same manner as theField 4 data of Table 5. However, because the human interest fields areless subjective and relate more directly to denotative context, in apreferred embodiment assigned editors are used to define most of thehuman interest fields. However several variables on the Table 3 list ofhuman interest fields, such as the miscellaneous fields for“Abstract-Concrete,” “Power,” and “Activity” are better left toevaluation by panels of connotative judges. These fields are defined asdescribed above for the field 4 data and are subject to the same orsimilar data integrity procedures.

A preferred embodiment of the invention such as the one described hereinis both human-judgment based and dynamic, reflecting the human anddynamic nature of language. Since the data provided by the connotativejudges are key to the system and method, one may wish to establish aprogram of continuous update of the database, either at prescribedintervals or on an ongoing basis, such as through a World Wide Web site.In this way, connotative judges would be able to supply datacontinuously, with turnover of connotative judges easily managed, andthe database, particularly the. connotative component, kept completelyup to date allowing for new or changing connotative associations.

In one embodiment participating judges periodically or aperiodicallyreceive a mini-database via e-mail or by logging onto a web site. Themini-database serves as the questionnaire allowing the judge to enter acode for the connotative association (see table 6) for a given emotionalcategory (see table 2). The results are then processed as describedabove for data integrity (see questionnaire processing 90 of FIG. 8 andrelated description).

By practicing the above method and system of the present invention, acomplete and accurate connotative language reference database 12 isconstructed in any language, which then can be used to constructconnotative equivalents of denotative language reference resources, suchas connotative dictionaries, connotative thesauruses, and connotativetext analysis tools. In addition, the anchored system of judgmentelicitation may be applied in any field requiring accuracy in theelicitation of qualitative data where Likert-type scaling is applicable.

Meritorious and Advantageous Effects

One advantage of the system for identifying connotative meanings is thatreliable associations, including connotative descriptions andintensities, are identified for given words and phrases in each of theirdenotative contexts. Another advantage is that the associations aremaintained over time with changes in the vernacular or otherchanges/occurrences affecting connotative association.

Although a preferred embodiment of the invention has been illustratedand described, various alternatives, modifications and equivalents maybe used. Therefore, the foregoing description should not be taken aslimiting the scope of the inventions which are defined by the appendedclaims.

What is claimed is:
 1. A computer readable storage medium for storing aconnotative language reference data base, comprising a plurality ofrecords, each record comprising: a first field for identifying a term; asecond field for identifying a denotative context for the term in thefirst field; and a connotative field which stores a code, the codecorresponding to an emotional descriptor, said emotional descriptorcorresponding to an emotional affect, the emotional affect being aconnotative meaning for said term.
 2. A computer readable storage mediumfor storing a connotative language reference data base, comprising aplurality of records, each record comprising: a first field foridentifying a term; a second field for identifying a denotative contextfor the term in the first field; a connotative field which stores acode, the code corresponding to one selection of a plurality ofpredefined connotative selections, said one selection corresponding to aconnotative meaning for said term, in which the connotative field is oneof a plurality of connotative fields for each record, each one of theplurality of connotative fields storing a code corresponding to oneselection of a plurality of predefined connotative selections, theplurality of predefined connotative selections comprising an indicatorof no connotative association and a plurality of sets of emotionaldescriptors, each one set of the plurality of sets corresponding to amutually exclusive one emotional category of a plurality of emotionalcategories.
 3. The medium of claim 2, in which there are no more thanone connotative field of the plurality of connotative fields associatedwith each one of the plurality of emotional categories.
 4. The medium ofclaim 2, in which there are two connotative fields of the plurality ofconnotative fields associated with each one of the plurality ofemotional categories—a first field of the two associated connotativefields storing a code for identifying a primary connotative selection, asecond field of the two associated connotative fields for storing a codefor identifying a secondary connotative selection, the primaryconnotative selection and the secondary connotative selection selectedfrom the plurality of predefined connotative selections.
 5. The mediumof claim 2, in which each record further comprises: a third field foridentifying the part of speech for the term as used in the denotativecontext identified by the second field.
 6. The medium of claim 2, inwhich each record further comprises: for each one connotative field ofthe plurality of connotative fields, an intensity field which identifiesan intensity rating for the connotative selection identified by the codein the corresponding one connotative field.
 7. The medium of claim 2, inwhich each record further comprises: a power field for identifying apower rating associated with the term.
 8. The medium of claim 2, inwhich each record further comprises: an activity seventh field foridentifying an activity rating for the term.
 9. The medium of claim 2,in which each record further comprises: an abstract field foridentifying a rating along an abstract to concrete rating scale for theterm.
 10. The medium of claim 2, in which each record further comprises:a plurality of contextual fields for identifying human interestcategories associated with the term.
 11. The computer readable storagemedium of claim 2, further comprising computer executable code means ofinstructions for processing a user input to search for a record amongthe plurality of records corresponding to the user input.
 12. The mediumof claim 11, which stores a plurality of filtering options, and whereinsaid code means comprises computer executable instructions forprocessing the user input to search for a record among the plurality ofrecords corresponding to a selection identified by the user input, theidentified selection identifying a filtering option from among theplurality of filtering options.
 13. A computer system for executing acomputer program implementing a connotative language reference, thesystem comprising: a data base having a plurality of records, eachrecord including: a first field for identifying a term; a second fieldfor identifying a denotative context for the term in the first field; aplurality of connotative fields, each one of the plurality ofconnotative fields storing a code corresponding to one selection of aplurality of predefined connotative selections, the plurality ofpredefined connotative selections comprising an indicator of noconnotative association and a plurality of sets of emotionaldescriptors, each one set of the plurality of sets corresponding to amutually exclusive one emotional category of a plurality of emotionalcategories; the system further comprising: means for displaying for agiven record, the term, the denotative context and at least oneselection of the plurality of predefined connotative selections amongthe plurality of connotative fields.
 14. The system of claim 13, inwhich each record of the data base further comprises: a contextual fieldfor identifying a human interest area associated with the term, theidentified human interest area being from a predefined set of humaninterest areas; the system further comprising: means for displaying aplurality of filtering options corresponding to predefined set of humaninterest areas; means for processing a selection of filtering options toidentify an output record from the data base which includes an entryamong the output record's plurality of contextual fields whichcorresponds to the selection of filtering options.
 15. The system ofclaim 13, in which each record of the data base further comprises: acontextual field for identifying a special diction area associated withthe term, the identified special diction area being from a predefinedset of special diction areas; the system further comprising: means fordisplaying a plurality of filtering options corresponding to predefinedset of special diction areas; means for processing a selection offiltering options to identify an output record from the data base whichincludes an entry among the output record's plurality of contextualfields which corresponds to the selection of filtering options.
 16. Thesystem of claim 13, in which each record of the data base furthercomprises: a power field for identifying a power rating associated withthe term; the system further comprising: means for displaying afiltering option corresponding to a scale of power ratings; means forprocessing a selection of filtering options to identify an output recordfrom the data base which includes an entry among the output record'splurality of contextual fields which corresponds to the selection offiltering options.
 17. The system of claim 13, in which each record ofthe data base further comprises: an activity power field identifying anactivity rating associated with the term; the system further comprising:means for displaying a filtering option corresponding to a scale ofactivity ratings; means for processing a selection of filtering optionsto identify an output record from the data base which includes an entryamong the output record's plurality of contextual fields whichcorresponds to the selection of filtering options.
 18. The system ofclaim 13, in which each record of the data base further comprises: anabstract field for identifying a rating along an abstract to concretescale, the rating being associated with the term; the system furthercomprising: means for displaying a filtering option corresponding to theabstract to concrete scale; means for processing a selection offiltering options to identify an output record from the data base whichincludes an entry among the output record's plurality of contextualfields which corresponds to the selection of filtering options.
 19. Thesystem of claim 13, in which each record of the data base furthercomprises: for each one of the plurality of connotative fields, anintensity field for identifying an intensity rating associated with thecorresponding connotative field; said displaying means for displayingthe intensity field for connotative selection of said given record. 20.The system of claim 13, further comprising: means for displaying aplurality of filtering options; means for processing a selection ofdisplayed filtering options to identify an output record from the database corresponding to the selection of filtering options.
 21. The systemof claim 13, further comprising: means for updating the data base tochange the connotative selection associated with the given record. 22.The system of claim 13, further comprising: means for displaying anemotional descriptor from multiples ones of said plurality of categoriesfor the given record and a depiction of a corresponding intensity valuefor said displayed emotional descriptor.
 23. The system of claim 13,further comprising a plurality of display placeholder variables, eachone of the plurality of display placeholder variables corresponding toone of the plurality of emotional categories and holding an emotionaldescriptor associated with the corresponding emotional category for thegiven record, said display means displaying the held emotionaldescriptors for the given record.
 24. The system of claim 13, furthercomprising: means for storing said plurality of predefined connotativeselections; and computer executable means of instructions forassociating each said code of said plurality of connotative fields to acorresponding one of said plurality of predefined connotativeselections.
 25. The system of claim 13, in which the power rating is thehuman interest term.